ArticleMedical physics2026
Photon minibeam-based LATTICE radiotherapy for small and medium-sized tumors: A dosimetric planning study.
Article in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Exploratory personalized radiobiological modeling of bystander and immune effects to inform SFRT-SBRT scheduling.Medical physics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundLattice radiotherapy (LRT) is a spatially fractionated technique that delivers three-dimensional high-dose vertices within tumors. However, conventional LRT is constrained by geometric limitations when applied to small and medium-sized tumor volumes, primarily due to the large beam sizes that restrict optimal lattice pattern formation. PURPOSE: This study aims to investigate a photon minibeam-based LATTICE radiotherapy (mini-LRT) approach designed to overcome the geometric limitations of conventional LRT and enable effective spatially fractionated treatment for small and medium-sized tumors adjacent to critical organs.
methodsThree brain cases and three lung cases, with clinical target volumes ranging from 12.34 cc to 40.88 cc, were presented for treatment planning comparison between conventional LRT and mini-LRT. A multi-collimator delivery strategy employing shifted slit patterns was implemented to achieve complementary spatial coverage. Dose calculation and optimization were performed using Monte Carlo simulations and solved via an iterative convex relaxation algorithm. Reference stereotactic body radiation therapy (SBRT) plans were generated for all six cases, and setup-error robustness analysis was performed for two representative cases using nominal and shifted dose-influence matrix scenarios.
resultsMini-LRT produced denser lattice structures in all cases, generating 5-11 vertices compared to only 1-3 vertices achievable with conventional LRT. Vertex diameters were reduced from 15.0 mm to 3.0-4.0 mm, and vertex-to-vertex distances decreased from 25.0 mm to 12.5 mm. The lattice volume ratio ranged from 0.68% to 1.07% with mini-LRT. Organs at risk (OARs) dose reductions were observed in the evaluated cases, including reduced mean dose to brainstem, heart, and esophageal. Furthermore, mini-LRT achieved a higher peak-to-valley dose ratio (PVDR) ranging from 2.19 to 2.94, compared to 1.75-2.34 for conventional LRT. Reference SBRT plans achieved clinical target volume (CTV) D
conclusionsThis proof-of-concept dosimetric planning study suggests that photon minibeam-based LATTICE radiotherapy can generate compact spatially fractionated dose distributions in selected small and medium-sized tumors. Compared with conventional LRT, mini-LRT increased vertex density, reduced lattice volume ratio, and improved OAR sparing in the evaluated cases. Additional experimental validation, motion assessment, and larger patient studies are required before clinical translation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.